A dynamic fuzzy neural network for short-term load forecasting of the Greek power system is proposed, and an hourly based prediction whole year performed. DBD-FELF (Dynamic Block-Diagonal Fuzzy Electric Load Forecaster) consists rules with consequent parts that are networks internal recurrence. These have a hidden layer, which pairs neurons feedback connections between them. The overall model p...

This paper presents an Intrusion Detection System (IDS) with the integration of multi agent systems and artificial intelligence techniques such as fuzzy logic controller (FLC), multi-layer perceptron (MLP) and adaptive neurofuzzy inference system (ANFIS). The paper introduces Network Intrusion Detection Systems (NIDS), which monitors the network traffic and detect any possible attacks. The syst...

In this study, we introduce general frame of MAny Connected Intelligent Particles Systems (MACIPS). Connections and interconnections between particles get a complex behavior of such merely simple system (system in system).Contribution of natural computing, under information granulation theory, are the main topics of this spacious skeleton. Upon this clue, we organize two algorithms involved a f...

An online auxiliary control was designed for Static Var Compensator (SVC) to improve the poorly damped oscillations in multi-machine power system subjected to small and large disturbances. This paper presents auxiliary control based on Adaptive NeuroFuzzy (ANF) control using triangular membership function. Such a model free based control does not require any prior information about the system a...

Information from different sensors can be fused in various ways. It is often difficult to choose the most suitable method for solving a fusion problem. In a measurement situation, the measured signal is often corrupted by disturbances (noise, etc.). It is, therefore, meaningless to compare crisp values without the corresponding uncertainty intervals. This paper describes a toolbox including nin...

The paper presents adaptation and optimization of the interaction structure of interactive systems by application of the control theory principles based on a fuzzy neural network. The interactive system is presented as a control system consisting of two parts: 1) plant of control or controlled plant (model of the real-life process) and 2) neurofuzzy-based feedback control algorithm. The last on...

This paper proposes an adaptive neurofuzzy interface system ANFIS approach to identify the real power transfer between generators. Based on solved load flow results, it first uses modified nodal equation method MNE to determine real power contribution from each generator to loads. Then the results of MNE method and load flow information are utilized to train the designed ANFIS. It also incorpor...

Two new feature selection methods are introduced, the first based on separability criterion, the second on consistency index that includes interactions between the selected subsets of features. Comparison of accuracy was made against information-theory based selection methods on several datasets training neurofuzzy and nearest neighbor methods on various subsets of selected features. Methods ba...

Conventional control algorithms used in pH control systems give inefficient performance, leading to use of large mixers. To improve the neutralization control process, an ANFIS based advanced controller has been proposed. In this paper, method of design of adaptive controller based on neurofuzzy technique is presented. The method uses ANFIS methodology to 1 / 4